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May 7, 2026Discover EducationOpen Access

The mechanisms of AI acceptance drivers on learning outcomes in higher education

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Authors

YXYubin XuSCShuxian ChenZJZhuoran Jiang

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Overview

Randomized trial examines AI acceptance influences on learning outcomes in university students, indicating pivotal factors for education enhancement.

Key Points

  • This study aims to explore how drivers of AI acceptance affect learning satisfaction, motivation, and capability in higher education.
  • Analyzed 522 survey responses from university students in China.
  • Utilized Partial Least Squares Structural Equation Modeling (PLS-SEM) for data analysis.
  • Focused on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework.
  • Performance expectancy and social influence significantly increase learning satisfaction.
  • Effort expectancy and facilitating conditions enhance learning motivation and satisfaction.
  • Facilitating conditions have the most substantial impact on learning capability.

Cite This Study

Xu et al. (2026) studied this question.

synapsesocial.com/papers/69fc2b608b49bacb8b347752https://doi.org/10.1007/s44217-026-01553-3
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